Special Issue on "Machine Learning Technologies for Big Data Analytics" at journal of Electronics (Q1 & IF=2.412)

Scope:
Big Data Analytics is one high-focus of data science and there is no doubt that big data are now quickly growing in all science and engineering fields. Big data analytics is the process of examining and analyzing massive and varied data that can help organizations make more-informed business decisions, especially, for uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information. Big Data has become essential as numerous organizations deal with massive amounts of specific information, which can contain useful information about problems such as national intelligence, cybersecurity, biology, fraud detection, marketing, astronomy, and medical informatics. Several promising machine learning techniques can be used for Big Data analytics including representation learning, deep learning, distributed and parallel learning, transfer learning, active learning, and kernel-based learning. In addition, Big Data analytics demands new and sophisticated algorithms based on machine learning techniques to treat data in real-time with high accuracy and productivity. The goal of this special issue is to discuss several critical issues related to learning from massive amounts of data and highlight current research endeavors and the challenges to big data, as well as shared recent advances in this research area. We solicit new contributions that have a strong emphasis on Machine Learning for Big Data Analytics.

Guest Editors:
Prof. Dr. Amir H. Gandomi
Prof. Dr. Fang Chen
Dr. Laith Abualigah

Manuscript Submission Information:
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open-access journal is 1500 CHF (Swiss Francs). A holiday season discount of 500 CHF on the article processing charge will be applied if your paper is submitted during 20 December 2020–5 January 2021. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords:
- Big data analytic
- Data science
- Machine learning
- Intelligent decisions
- Knowledge discovery
- Deep learning
- Evolutionary computation
- Benchmarks for big data analysis
- Analysis of real-time data
- Real-world applications of machine learning